[DOC] Warn users about Peaks2MapsKernel and KDA Estimator (#420)

* Add warning to Peaks2MapsKernel.

* Add warning to KDA estimator.

* Update nimare/meta/cbma/mkda.py

* Fix KDA warning.

Author: tsalo

nimare/meta/cbma/mkda.py

@@ -462,6 +462,12 @@ class KDA(CBMAEstimator):
 
     Available correction methods: :func:`KDA.correct_fwe_montecarlo`
 
+    Warning
+    -------
+    The KDA algorithm has been replaced in the literature with the MKDA algorithm.
+    As such, this estimator should almost never be used, outside of systematic
+    comparisons between algorithms.
+
     References
     ----------
     .. [1] Wager, Tor D., et al. "Valence, gender, and lateralization of
@@ -476,6 +482,12 @@ class KDA(CBMAEstimator):
     def __init__(
         self, kernel_transformer=KDAKernel, null_method="empirical", n_iters=10000, **kwargs
     ):
+        LGR.warning(
+            "The KDA algorithm has been replaced in the literature with the MKDA algorithm. "
+            "As such, this estimator should almost never be used, outside of systematic "
+            "comparisons between algorithms."
+        )
+
         if not (isinstance(kernel_transformer, KDAKernel) or kernel_transformer == KDAKernel):
             LGR.warning(
                 f"The KernelTransformer being used ({kernel_transformer}) is not optimized "

nimare/meta/kernel.py

@@ -319,12 +319,21 @@ class Peaks2MapsKernel(KernelTransformer):
     resample_to_mask : :obj:`bool`, optional
         If True, will resample the MA maps to the mask's header.
         Default is True.
+
+    Warning
+    -------
+    Peaks2MapsKernel is not intended for serious research.
+    We strongly recommend against using it for any meaningful analyses.
     """
 
     def __init__(self, model_dir="auto"):
         # Use private attribute to hide value from get_params.
         # get_params will find model_dir=None, which is *very important* when a path is provided.
         self._model_dir = model_dir
+        LGR.warning(
+            "The Peaks2Maps kernel transformer is not intended for serious research. "
+            "We strongly recommend against using it for any meaningful analyses."
+        )
 
     def _transform(self, mask, coordinates):
         transformed = []